Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/31505
Title: Edge detection using simplified Gabor wavelets
Authors: Jiang, W
Lam, KM 
Shen, T
Keywords: Edge detection
Gabor wavelets
Simplified Gabor wavelets
Issue Date: 2008
Publisher: IEEE
Source: 2008 International Conference on Neural Networks and Signal Processing, 7-11 June 2008, Nanjing, p. 586-591 How to cite?
Abstract: Gabor wavelets (GWs) have been commonly used for extracting local features for various applications, such as recognition, tracking, and edge detection. However, extracting the Gabor features is computationally intensive, so the features may be impractical for real-time applications. In this paper, we propose a set of simplified version of Gabor wavelets (SGWs) for edge detection. Experimental results show that our SGW-based edge detection algorithm can achieve a similar performance level to that using GWs, while the runtime required for feature extraction using SGWs is faster than that with GWs with the use of the fast Fourier transform (FFT). When compared to the Canny and other conventional edge detection methods, our proposed method can achieve a better performance in the terms of detection accuracy and computational complexity.
URI: http://hdl.handle.net/10397/31505
ISBN: 978-1-4244-2310-1
978-1-4244-2311-8 (E-ISBN)
DOI: 10.1109/ICNNSP.2008.4590418
Appears in Collections:Conference Paper

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